M. Lang
Impact in
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- Ecology and Vegetation Dynamics Studies
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- Parkinson's Disease Mechanisms and Treatments
- Neurological disorders and treatments
Papers in
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- Speech and dialogue systems 5
- AI-based Problem Solving and Planning 4
- Natural Language Processing Techniques 3
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- Advanced Vision and Imaging 4
- Co-authors
- Sandra Hirche (7 shared papers)Harald Albrecht (1 shared paper)Markus Wagner (1 shared paper)Wendelin Feiten (3 shared papers)Bernd Radig (3 shared papers)Dana Kulić (2 shared papers)Urban M. Fietzek (2 shared papers)Satoshi Endo (2 shared papers)
In The Last Decade
M. Lang
22 papers receiving 294 citations
Peers
Comparison fields: 5 of 81
- Nature and Landscape Conservation 54
- Neurology 63
- Computer Vision and Pattern Recognition 68
- Ecology, Evolution, Behavior and Systematics 47
- Plant Science 63
Countries citing papers authored by M. Lang
This map shows the geographic impact of M. Lang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by M. Lang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Lang more than expected).
Fields of papers citing papers by M. Lang
This network shows the impact of papers produced by M. Lang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by M. Lang. The network helps show where M. Lang may publish in the future.
Co-authors
The 23 scholars most cited alongside M. Lang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 79 | |
| 2 | 2020 | 54 | |
| 3 | 2015 | 21 | |
| 4 | 2019 | 16 | |
| 5 | Rigid motion estimation using mixtures of projected Gaussians | 2013 | 14 |
| 6 | 2014 | 14 | |
| 7 | 2002 | 12 | |
| 8 | 2019 | 12 | |
| 9 | 2017 | 10 | |
| 10 | 2015 | 9 | |
| 11 | 2002 | 9 | |
| 12 | MPG - Fast Forward Reasoning on 6 DOF Pose Uncertainty | 2012 | 8 |
| 13 | 1994 | 8 | |
| 14 | Real-Time 3D and Color Camera | 2001 | 8 |
| 15 | 2017 | 8 | |
| 16 | 2002 | 7 | |
| 17 | 2003 | 5 | |
| 18 | MPG - A Framework for Reasoning on 6 DOF Pose Uncertainty | 2017 | 3 |
| 19 | 2002 | 3 | |
| 20 | 2002 | 2 |
About M. Lang
M. Lang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Neurology and Instrumentation, having authored 25 papers that have together received 308 indexed citations. Recurring topics across this work include Speech and dialogue systems (5 papers), AI-based Problem Solving and Planning (4 papers), Advanced Vision and Imaging (4 papers), Natural Language Processing Techniques (3 papers), Robot Manipulation and Learning (3 papers), Parkinson's Disease Mechanisms and Treatments (3 papers), Robotic Mechanisms and Dynamics (3 papers) and Advanced Optical Sensing Technologies (3 papers). The work is most often cited by research in Nature and Landscape Conservation (54 citations), Neurology (63 citations), Computer Vision and Pattern Recognition (68 citations), Ecology, Evolution, Behavior and Systematics (47 citations) and Plant Science (63 citations). M. Lang has collaborated with scholars based in Germany, Canada and France. Frequent co-authors include Sandra Hirche, Harald Albrecht, Markus Wagner, Wendelin Feiten, Bernd Radig, Dana Kulić, Urban M. Fietzek, Satoshi Endo, Johannes Müller and Terry Taewoong Um. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Scientific Reports, Physiological Research, Ecological Engineering and IEEE Robotics and Automation Letters.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.